Management Approach in Analysis of Financial Distress in the Industrial and Mine Industries of Iran By Using Machine Learning Methods (NSGA-II, ABC)

Predicting financial distress is an important phenomenon for investors, creditors and other users of financial information. Determining the probability of a company’s distress before occurrence of distress and bankruptcy is considered as a very interesting and attractive subject and can be useful for both managers, and investors and creditors. In this study, using the data of 1350 year- company in the period 2008 to 2016 in industry and mining sector in Iran, the factors affecting financial distress and predicting it through Intelligence Algorithms methods (NSGA-II,ABC) have been studied. The results of the research indicate the indirect effect of the ratio of non-executive directors and the proportion of institutional owners and the direct effect of earnings management and management overconfidence on financial distress among other management variables. Also, the results show that the artificial intelligence algorithm can predict financial distress using management indicators and the ability of the ABC algorithm from NSGA-II algorithm to predict financial distress is higher.

Article Type:
Research/Original Article
Commercial Surveys, Volume:17 Issue:96, 2019
38 - 55  
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